
Absolutely Interdisciplinary returns this spring to explore new frontiers in AI research
The Schwartz Reisman Institute’s annual academic conference Absolutely Interdisciplinary returns for 2025 to explore interdisciplinary approaches to AI governance, risk and safety.
What’s Next After AIDA?
In the wake of AIDA’s death and with a federal election on the horizon, a key question has emerged: what’s next for Canada after AIDA?
Unequal outcomes: Tackling bias in clinical AI models
A new study by SRI Graduate Affiliate Michael Colacci sheds light on the frequency of biased outcomes when machine learning algorithms are used in healthcare contexts, advocating for more comprehensive and standardized approaches to evaluating bias in clinical AI.
Upcoming SRI Seminars showcase new insights on cutting-edge AI research
The SRI Seminar Series returns for 2025 with leading experts exploring AI’s impacts from a wide range of disciplines, including computer science, psychology, law, philosophy, and communication.
Information about our world: SRI/BKC workshop explores issues in access to platform data
What kinds of solutions should we consider for gaining access to data, and which purposes can justify this access? These and related questions were the topic of an event co-hosted by SRI and the Berkman Klein Center’s Institute for Rebooting Social Media at Harvard University coordinated by Lisa Austin.
Humans and LLMs: Partners in problem-solving for an increasingly complex world
A recent hackathon and symposium co-sponsored by SRI and U of T's Data Sciences Institute explored new ways of using large language models responsibly, with students and faculty receiving training on how to design efficient, interdisciplinary solutions to promote responsible AI usage.
Making big leaps with small models: What are small language models and super tiny language models?
The size of language models significantly impacts their adoption and usage. SRI Policy researcher Jamie A. Sandhu explores how small models are making big impacts in the field of AI.
SRI partners with Data Sciences Institute on “Toward a Fair and Inclusive Future of Work with ChatGPT”
Despite the growing use of ChatGPT, we lack a method to evaluate its performance and potential risks. SRI Associate Director Lisa Austin, Faculty Fellow Shion Guha, and Faculty Affiliates Anastasia Kuzminykh and Shurui Zhou are setting out to study and analyze the impact of generative AI on a wide range of communities. Learn more about "Toward a Fair and Inclusive Future of Work with ChatGPT."
SRI Seminar Series returns to explore new questions at the intersection of technology and society
The SRI Seminar Series returns for fall 2024 with leading experts across various fields, including computer science, communications, law, healthcare, and philosophy. Seminars will explore new questions at the intersection of technology and society through critical issues such as trust, inequality, public policy, and the ethical implications of AI systems.
What might the Canadian AI Safety Institute look like? Reflections on an emerging national AI safety regime
In April 2024, the Government of Canada pledged $2.4bn toward AI in its annual budget, including $50m for a new AI Safety Institute. What scope, expertise, and authority will the new institute need to achieve its full potential? We examine the early approaches of similar institutes in the UK, US, and EU.
From mourning to machine: Griefbots, human dignity, and AI regulation
Griefbots are artificial intelligence programs designed to mimic deceased individuals by using their digital footprint. Griefbots raise significant concerns about data collection and implications to human dignity. This article explores the digital afterlife industry and the ethical and legal challenges it presents, including a consideration of health, privacy, and property laws in Canada.
The smart way to run smart cities: New report explores data governance and trusted data sharing in Toronto
A new report from SRI Research Lead Beth Coleman, SRI Graduate Fellow Madison Mackley, and collaborators explores questions such as: How can we facilitate data-sharing across divisions to improve public policy and service delivery? What are the risks of data-sharing, how can we mitigate those risks, and what are the potential benefits of doing it right?